Contrary to the hype, AI isn't a substitute for human thought. It's a powerful pattern-matching tool that consumes vast data. A growing problem is that AI is increasingly training on its own regurgitated output, creating a closed loop that lacks genuine novelty or external grounding.

Modern AI can rapidly build complex products ("zero to n"), but it lacks the human intuition to simplify by removing features. This critical skill, honed through real-world usage and experience, is what prevents products from becoming bloated and unfocused.

The debate over whether LLMs are truly "intelligent" is academic. The practical test for product builders is whether the tool produces valuable outputs that lead to better decisions, regardless of the underlying mechanism.

The speed and simplicity of AI development tools have led to a surge in 'vibe coded' products. These applications are often fun to build and appear impressive but lack the rigorous product thinking and engineering discipline required for long-term viability and maintenance.

The concept of "taste" is demystified as the crucial human act of defining boundaries for what is good or right. An LLM, having seen everything, lacks opinion. Without a human specifying these constraints, AI will only produce generic, undesirable output—or "AI slop." The creator's opinion is the essential ingredient.

The core problem with many AI models is "slop"—the endless repetition of low-quality, generic content. Taste Labs aims to solve this by building a community of human experts to provide curated, high-quality data, thereby raising the quality bar for AI-generated output.

Many people struggle to define what 'good' looks like. Building an evaluation (eval) for an AI system requires you to codify your quality standards, forcing a level of clarity and commitment that improves your own process and the AI's output.

Blindly applying AI to every task results in low-quality, untrustworthy output ("slop"). The optimal approach involves using AI as an accelerator while retaining human oversight for prompting, verification, and critical judgment. Over-reliance on the AI shortcut diminishes quality and trust.

AI can generate output, but it cannot discern what is truly 'good.' To create high-quality, differentiated content, humans must cultivate their own sense of taste by actively consuming excellent writing and journalism. This discernment is the key human advantage over automation.